class_docstr: This class ensembles the output from multiple BiDAF models.
  
  It combines results from the submodels by averaging the start and end span probabilities.
class_docstr_tok: ["This","class","ensembles","the","output","from","multiple","BiDAF","models",".","It","combines","results","from","the","submodels","by","averaging","the","start","and","end","span","probabilities","."]
code: def get_metrics(self, reset=False):
      exact_match, f1_score = self._squad_metrics.get_metric(reset)
      return {
          "em": exact_match,
          "f1": f1_score,
      }
  
file_path: magnitude/pymagnitude/third_party/allennlp/models/reading_comprehension/bidaf_ensemble.py
imports: from __future__ import division
  from __future__ import absolute_import
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.models.ensemble import Ensemble
  from allennlp.models.archival import load_archive
  from allennlp.models.model import Model
  from allennlp.models.reading_comprehension.bidaf import BidirectionalAttentionFlow
  from allennlp.common import Params
  from allennlp.data import Vocabulary
  from allennlp.training.metrics import SquadEmAndF1
label_desc: Use image node_id 3 for calling the BidafEnsemble obj's underlying member method code with example usage: obj.get_metrics(reset) and returns: dict